Product design question
How would you build a product on Facebook for blood donation?
- Meta
- Product design
- Medium
Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.
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What this question tests
Product sense for a real, sensitive feature area, balancing urgency, trust, and logistics.
How to approach it
- Identify the core problem, matching willing donors with urgent, nearby blood needs quickly, since blood has a short shelf life and type matching matters.
- Identify the target users, people needing blood or posting on behalf of a patient, and potential donors nearby with the right blood type.
- Propose the core mechanism, a donor request post that notifies nearby users with a matching blood type.
- Address trust and spam, verification through blood banks or hospitals to prevent fraudulent requests.
- Define success metrics, percentage of urgent requests matched with a donor within a target time window, for example 24 hours.
What a strong answer includes
- Names the real time sensitivity constraint of blood needs, distinct from a generic donation marketplace, and designs around fast, nearby matching.
- Proposes a concrete trust mechanism, verification via partner blood banks or hospitals for urgent requests, to prevent abuse of a sensitive feature.
- Sets a meaningful outcome metric, percent of requests matched within 24 hours, rather than just number of donor sign ups.
Common mistakes
- Designing this like a generic social post with no attention to blood type matching or urgency.
- No fraud or verification mechanism for a feature that could be abused or misused.
- No time bound success metric appropriate to how urgent blood needs actually are.
Likely follow-up questions
- How would you prevent this feature from being used for scams or fraud?
- How would you handle a request in an area with very few registered donors nearby?
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Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 4: Discovery and strategy for AI products
- Chapter 7: AI UX and human oversight: design for a system that is wrong sometimes
- Chapter 14: Get the job: the AI PM interview loop